A method includes acquiring timing analysis data associated with a cell and activity data of one or more inputs of the cell, determining a glitch toggle rate for an output of the cell based on the activity data of the one or more inputs of the cell and the timing analysis data, and estimating a glitch power based on at least the glitch toggle rate.
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3. The method of claim 1, wherein the activity data includes a static probability and a toggle rate of the one or more inputs of the cell.
This invention relates to a method for analyzing and modeling the behavior of inputs in a cell, particularly in the context of biological or computational systems. The method addresses the challenge of accurately predicting or simulating the dynamic behavior of cellular inputs, which is critical for applications in systems biology, synthetic biology, and bioengineering. The method involves collecting activity data for one or more inputs of the cell, where the activity data includes both a static probability and a toggle rate of the inputs. The static probability represents the likelihood of an input being active or inactive in a steady state, while the toggle rate indicates how frequently the input switches between active and inactive states over time. By incorporating both metrics, the method provides a more comprehensive understanding of input behavior compared to approaches that rely solely on static probabilities or dynamic rates alone. The method may also include steps such as generating a model of the cell based on the activity data, where the model simulates the interactions between inputs and their effects on cellular processes. This model can then be used to predict cellular responses under different conditions, optimize input configurations, or design synthetic biological circuits. The inclusion of both static and dynamic metrics allows for more accurate simulations, particularly in systems where inputs exhibit stochastic or time-varying behavior. The method is applicable to various types of inputs, including gene expression regulators, signaling molecules, or environmental stimuli, and can be implemented in computational frameworks or experimental setups.
4. The method of claim 1, wherein the glitch toggle rate is determined based on a binary decision diagram (BDD), the BDD representing a function of the cell.
This invention relates to digital circuit design, specifically methods for analyzing and optimizing glitch behavior in digital circuits. Glitches, which are unwanted transient voltage spikes, can cause timing errors and power inefficiencies. The invention addresses the challenge of accurately predicting and controlling glitch propagation in digital circuits, particularly in complex designs where traditional simulation methods are computationally expensive. The method involves determining the glitch toggle rate—a metric indicating the frequency of glitch occurrences—for a given circuit cell using a binary decision diagram (BDD). A BDD is a compact data structure representing Boolean functions, enabling efficient analysis of logical relationships in digital circuits. By modeling the cell's behavior as a function in the BDD, the method can systematically evaluate how input transitions propagate through the cell and generate glitches. This approach allows for precise calculation of the glitch toggle rate without exhaustive simulation, improving efficiency in circuit verification and optimization. The method may also include steps to construct the BDD from the cell's logical function, ensuring accurate representation of its behavior. The BDD-based analysis can be applied to individual cells or entire circuit paths, providing insights into glitch propagation across multiple stages. This technique is particularly useful in high-performance and low-power designs where minimizing glitches is critical for reliability and energy efficiency. The invention enhances existing circuit analysis tools by integrating BDD-based glitch modeling, enabling faster and more accurate glitch characterization.
8. The method of claim 7, wherein a width of the adjusted timing window is a function of a cell delay, a clock period, or a threshold value.
This invention relates to timing window adjustment in integrated circuit design, specifically addressing the challenge of optimizing timing margins in digital circuits to improve performance and reduce power consumption. The method involves dynamically adjusting the width of a timing window used for data sampling or signal propagation based on specific circuit parameters. The timing window width is determined as a function of a cell delay, a clock period, or a predefined threshold value. By dynamically adjusting the timing window, the method ensures that data is sampled or propagated at optimal times, reducing timing violations and improving circuit reliability. The cell delay refers to the propagation delay through a logic gate or cell, while the clock period represents the time between clock cycles. The threshold value may be a predefined limit set by design constraints or performance requirements. This adjustment mechanism allows for finer control over timing margins, enabling more efficient circuit operation and better adaptation to process variations or environmental changes. The method can be applied in various digital circuits, including high-speed processors, memory interfaces, and communication systems, where precise timing control is critical. By dynamically adjusting the timing window, the invention helps mitigate timing errors, enhances signal integrity, and optimizes power efficiency.
10. The method of claim 7, wherein the adjusted timing window includes an area of the timing window having a high probability density for the arrival times of the input signals associated with the one or more inputs of the cell.
This invention relates to timing optimization in digital circuits, specifically addressing the challenge of accurately capturing input signals in high-speed integrated circuits where signal arrival times vary due to process, voltage, and temperature variations. The method involves adjusting a timing window for signal capture based on statistical analysis of signal arrival probabilities. A cell in the circuit receives multiple input signals, each with inherent timing uncertainties. The method first determines a timing window for capturing these signals, then refines this window by identifying regions with high probability densities for signal arrivals. By focusing on these high-probability regions, the method improves signal capture reliability while reducing power consumption and timing errors. The adjustment process may involve dynamically modifying the window's position, width, or shape based on real-time or pre-characterized probability distributions. This approach is particularly useful in asynchronous or clockless circuits where precise timing control is critical. The invention enhances performance by minimizing metastability risks and optimizing the trade-off between speed and power efficiency in digital systems.
12. The method of claim 1, wherein the glitch toggle rate includes functional toggles and glitch toggles propagated for two or less levels.
A method for analyzing and optimizing digital circuit behavior focuses on reducing power consumption and improving reliability by controlling signal toggling in integrated circuits. The method addresses the problem of excessive power dissipation caused by unnecessary signal transitions, including both functional toggles (intentional state changes) and glitch toggles (unintended transient transitions). Glitch toggles, which occur due to propagation delays and logic interactions, contribute significantly to power loss and timing errors. The method specifically targets glitch toggles that propagate through two or fewer logic levels, as these are more likely to be mitigated without disrupting circuit functionality. By monitoring and selectively suppressing these toggles, the method reduces dynamic power consumption while maintaining signal integrity. The approach involves analyzing signal paths, identifying glitch-prone regions, and applying optimization techniques such as gate sizing, clock gating, or logic restructuring to minimize unwanted transitions. This method is particularly useful in high-performance and low-power digital designs, where power efficiency and timing accuracy are critical. The solution ensures that only necessary signal changes occur, thereby improving energy efficiency and circuit reliability.
15. The system of claim 13, wherein the activity data includes a static probability and a toggle rate of the one or more inputs of the cell.
A system for analyzing and optimizing cell behavior in electronic circuits, particularly for memory cells or logic gates, addresses the challenge of accurately predicting and controlling cell state transitions. The system monitors and processes activity data of one or more inputs of a cell to determine its operational characteristics. The activity data includes a static probability, representing the likelihood of the input remaining in a stable state, and a toggle rate, indicating the frequency of state changes. By analyzing these metrics, the system enables dynamic adjustments to improve performance, reduce power consumption, or enhance reliability. The system may integrate with other components, such as error correction modules or power management units, to leverage the activity data for broader circuit optimization. This approach is particularly useful in applications where cell behavior must be precisely controlled, such as in memory arrays, digital signal processing, or adaptive computing architectures. The inclusion of static probability and toggle rate provides a comprehensive view of input behavior, allowing for more informed decision-making in circuit design and operation.
16. The system of claim 13, wherein the glitch toggle rate is determined based on a binary decision diagram (BDD), the BDD representing a function of the cell.
This invention relates to digital circuit design, specifically addressing the challenge of optimizing glitch behavior in digital circuits to improve performance and reduce power consumption. Glitches, which are unwanted transient voltage spikes, can degrade circuit reliability and increase power dissipation. The system determines the glitch toggle rate—a measure of glitch frequency—using a binary decision diagram (BDD). The BDD represents a logical function of a circuit cell, allowing efficient analysis of glitch propagation and interaction with other circuit elements. By leveraging the BDD, the system can model and predict glitch behavior under different input conditions, enabling designers to identify and mitigate problematic glitches. The BDD-based approach provides a structured way to analyze complex logical relationships, improving accuracy and computational efficiency compared to traditional methods. This technique is particularly useful in high-performance and low-power digital circuit design, where minimizing glitches is critical for meeting performance and energy efficiency targets. The system integrates this analysis into the circuit design process, allowing for early detection and correction of glitch-related issues.
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August 25, 2021
June 4, 2024
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